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<p>The rising demand for wind power generation has spurred interest in brushless doubly-fed reluctance generators (BDFRGs) as a more efficient, low-maintenance alternative to traditional doubly-fed induction generators. This study introduces a sensorless speed control technique for BDFRGs that integrates primary field-oriented control with a novel model reference adaptive system (MRAS) based on a modified fictitious quantity method (<i>mX</i><sub><i>s</i></sub>-MRAS). The proposed MRAS algorithm is parameter-independent and eliminates the need for integrator and differentiator components, enhancing robustness and adaptability across diverse operating conditions. Performance is compared with conventional <i>X</i><sub><i>s</i></sub>-MRAS in MATLAB/Simulink, with additional stability and the effects of parameter mismatch analyses confirming the system’s robustness. Experimental tests on a 1.6&#xa0;kW BDFRG prototype further validate the stable performance of the proposed control method, underlining its potential for advancing sensorless control in wind power applications through increased efficiency and reduced maintenance.</p>

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Robust and adaptive speed control for BDFRGs: a novel MRAS-based sensorless approach for wind power applications

  • 期刊论文

  • 发表日期：

    2025年5月6日

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  • Mukesh Kumar,
  • Abhisek Pal

摘要

The rising demand for wind power generation has spurred interest in brushless doubly-fed reluctance generators (BDFRGs) as a more efficient, low-maintenance alternative to traditional doubly-fed induction generators. This study introduces a sensorless speed control technique for BDFRGs that integrates primary field-oriented control with a novel model reference adaptive system (MRAS) based on a modified fictitious quantity method (mXs-MRAS). The proposed MRAS algorithm is parameter-independent and eliminates the need for integrator and differentiator components, enhancing robustness and adaptability across diverse operating conditions. Performance is compared with conventional Xs-MRAS in MATLAB/Simulink, with additional stability and the effects of parameter mismatch analyses confirming the system’s robustness. Experimental tests on a 1.6 kW BDFRG prototype further validate the stable performance of the proposed control method, underlining its potential for advancing sensorless control in wind power applications through increased efficiency and reduced maintenance.